Abstract
Joint estimation of groundwater contaminant source characteristics and hydraulic conductivity is of great significance for contaminant transport models in heterogeneous subsurface media. As for accurate characterization of hydraulic conductivities, both geostatistical modeling and groundwater inverse modeling are alternative approaches. In this study, an iterative ensemble smoother and sequential gaussian simulation (SGSIM) in geostatistics modeling were combined to realize the simultaneous inversion of contaminant sources and hydraulic conductivities, by using directly measured hydraulic conductivities and indirect hydraulic head and concentration data. To alleviate the high computational cost caused by repetitive evaluations of complex, high-dimensional groundwater models, SGSIM with the pilot points method was used. Considering the characteristics of the proposed method, four scenarios with ten cases were set up in terms of ensemble number and iteration number that affect the performance of the iterative ensemble smoother, the number of pilot points, and the observation data, respectively. The results for the synthetic example indicate that the ensemble size of 2000 and the pilot point number of 80 is an ideal combination of parameters, and the proposed method can successfully recover contaminant source information simultaneously with hydraulic conductivity.
Highlights
Introduction iationsTo implement the remediation strategy in the contaminated groundwater, it is critical to accurately estimate the key parameters of the groundwater contaminant transport model
That affect the performance of the iterative local updating ensemble smoother (ILUES) algorithm, the number of pilot points (n p ) of the sequential gaussian simulation (SGSIM) method, and the observation data, respectively
In other cases, measured conductivities (K), hydraulic head and concentration data collected from observation wells, together with the conductivities at pilot points, were used to update the conductivities ensemble and contaminant source parameters
Summary
To implement the remediation strategy in the contaminated groundwater, it is critical to accurately estimate the key parameters (the location and strength of the contaminant sources) of the groundwater contaminant transport model. The hydraulic conductivity usually needs to be identified because of its close relationship with the contaminant transport. As for accurate characterization of hydraulic conductivities, geostatistical modeling is an effective solution to characterize spatial variability and predict the property of interest at unsampled locations. Geostatistical methods based on directly measured hydraulic conductivities do not give good results at model validation [1]. Known as a stochastic inverse method, in which the parameters of groundwater model are considered as random
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